Data Science on Azure

© Elephant Scale

Jan. 06, 2020

Overview

Data Science includes statistics, data visualization and exploration,
and Machine learning. Since Microsoft Azure is the second-largest cloud computing provider, knowledge of its Data Science capabilities is essential for
building best-of-breed solutions. Azure’s particular strength is in the usability and integration with the Microsoft stack.

In this course, the students will get an overview of ML with Python and R, the two standard environments for ML. They will also learn the specifics of the Azure and the capabilities that it offers to ML developers.

One of the goals of the course is to prepare the students for taking the Azure certification exam.

What you will learn

  • The basic of the two most popular data science languages, R and Python
  • Azure Machine Learning and Data Science IDE
  • Spark and Databricks runtime
  • Machine Learning
  • Streaming analytics

Audience

Developers, Architects

Duration

4 days

Format

Lectures and hands-on labs. (50%, 50%)

Prerequisites

  • Interest in Machine Learning (Machine Learning overview is included in the course)
  • Familiarity with Python or R is a plus

Lab environment

  • A reasonably modern laptop
  • Unrestricted connection to the Internet. Laptops with overly restrictive VPNs or firewalls may not work properly
  • Chrome browser
    • SSH client for your platform

Detailed outline

Introduction to Machine Learning

    • Machine Learning Concepts
    • Machine Learning Approaches
    • Supervised Learning
    • Unsupervised Learning
    • Machine Learning Life Cycle
    • Machine Learning Languages and Platforms

Introduction to R

    • Installing RStudio, Installing Packages
    • R Data Structure
    • Vector, Factor, Lists, Data Frames
    • R for Statistical Analysis
    • R for Machine Learning
    • R for Visualization

Introduction to Python

    • Python IDE
    • Install Packages
    • Python for Statistical Summary
    • Statistical Distribution
    • Python for Visualization
    • Python for Machine Learning

R Visualization in Power BI

    • Power BI
    • Setting Up R in Power BI
    • Writing R Code in Power BI
    • R Features in Power BI
    • Slice and Dice
    • Edit R Code in RStudio
    • Predictive Analysis in Power Query with R
    • Neural Networks
    • Decision Trees
    • Automated Machine Learning Inside Power Query

Azure Databricks – Spark

    • Databricks Environment
    • Machine Learning on Databricks
    • Linear Regression
    • Logistic Regression
    • SVN
    • Decision Trees, Random Forests

Machine Learning in Azure

    • R in Azure Data Lake
    • Azure Data Lake Environment
    • Running R Scripts in U-SQL
    • Azure Machine Learning Studio

Machine Learning in Azure Stream Analytics

    • Event Hub
    • Application
    • Azure Stream Analytics
    • Azure Machine Learning (ML) Workbench

Data Science Virtual Machine and AI Frameworks

    • Deep Learning Tools with Cognitive Toolkit